update hf link

app.py

@@ -141,8 +141,7 @@ def run_model(target_dir, model, anchor_size=100) -> dict:
 
     # Clean up
     torch.cuda.empty_cache()
-    for k,v in predictions.items():
-        print(f"{k}: {v.shape if isinstance(v, np.ndarray) else type(v)}")
+
     return predictions
 
 
@@ -271,7 +270,8 @@ def gradio_demo(
     print("Running run_model...")
     with torch.no_grad():
         predictions = run_model(target_dir, model)
-
+    for k,v in predictions.items():
+        print(f"{k}: {v.shape if isinstance(v, np.ndarray) else type(v)}")
     # Save predictions
     prediction_save_path = os.path.join(target_dir, "predictions.npz")
     np.savez(prediction_save_path, **predictions)